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  1. 81
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    Quality Prediction of Web Services Based on a Covering Algorithm by Ying Jin, Guangming Cui, Yiwen Zhang

    Published 2020-01-01
    “…In this paper, we propose UIQPCA, a novel approach for hybrid User and Item-based Quality Prediction with Covering Algorithm. UIQPCA integrates information of both users and Web services on the basis of users’ ideas on the quality of coinvoked Web services. …”
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    Article
  3. 83
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    A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

    Published 2025-06-01
    “…This data can provide valuable insights into the behavior of a specific machine, enabling optimization or the prediction of potential malfunctions. Supervised machine learning algorithms are capable of predicting the remaining useful life (RUL) of a machine. …”
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  5. 85
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    Computerised Method of Multiparameter Optimisation of Predictive Control Algorithms for Asynchronous Electric Drives by Grygorii Diachenko, Serhii Semenov, Katarzyna Marczak, Gernot Schullerus, Ivan Laktionov

    Published 2025-07-01
    “…This paper proposes a computerised method for the multiparameter optimisation of predictive control algorithms for asynchronous electric drives. …”
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  7. 87

    Aquaculture Prediction Model Based on Improved Water Quality Parameter Data Prediction Algorithm under the Background of Big Data by Yuan Jiang, Fei Yan

    Published 2022-01-01
    “…Considering the complex relationship between dissolved oxygen and water quality, combined with principal component analysis, a PCA-BP (principal component analysis back propagation) water quality prediction model was proposed. The parameters of PCA-BP water quality prediction model were optimized by genetic algorithm, the threshold and weight of BP neural network were determined, and an improved PCA-BP water quality prediction model was constructed. …”
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    Predicting agricultural drought in central Europe by using machine learning algorithms by Endre Harsányi

    Published 2025-04-01
    “…The findings of this research promote RF as a reliable algorithm for predicting SPEI droughts.…”
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    Article
  11. 91

    Prediction of growth and feed efficiency in mink using machine learning algorithms by A. Shirzadifar, G. Manafiazar, P. Davoudi, D. Do, G. Hu, Y. Miar

    Published 2025-02-01
    “…The XGB algorithm can be an accurate algorithm to predict the ADG, FCR, and RFI values without measuring costly daily feed intake. …”
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    Article
  12. 92

    Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

    Published 2025-03-01
    “…Predicting ecological communities is highly challenging but necessary to establish effective conservation and monitoring programs. …”
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    Article
  13. 93

    Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

    Published 2022-04-01
    “…There were no differences between the means of actual and predicted LWs by machine learning models. The fact that the models generalized well on the testing data sets indicates that machine learning algorithms have valid predictive patterns and are effective methods in LW weight of Norduz sheep. …”
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    PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

    Published 2022-11-01
    “…One of those areas is the prediction and prevention of consumer churn. There are two basic types of consumer churn, complete churn and partial churn. …”
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  16. 96

    Phase diagram construction and prediction method based on machine learning algorithms by Shengkun Xi, Jiahui Li, Longke Bao, Rongpei Shi, Haijun Zhang, Xiaoyu Chong, Zhou Li, Cuiping Wang, Xingjun Liu

    Published 2025-05-01
    “…Meanwhile, the CALPHAD method has accumulated abundant high-quality phase diagram data who would be the perfect training data for the machine learning algorithms. In the present work, a phase diagram prediction method which integrates machine learning algorithms with CALPHAD descriptors is proposed. …”
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  17. 97

    A Comparative Analysis of Machine Learning Algorithms in Energy Poverty Prediction by Elpida Kalfountzou, Lefkothea Papada, Christos Tourkolias, Sevastianos Mirasgedis, Dimitris Kaliampakos, Dimitris Damigos

    Published 2025-02-01
    “…The present paper adds new insights to the existing literature by exploring the capacity of ML algorithms to successfully predict energy poverty, as defined by different indicators, for the case of the “Urban Region of Athens” in Greece. …”
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  18. 98

    Comparative Study for Classification Algorithms Performance in Crop Yields Prediction Systems by Halbast Rashid Ismael, Adnan Mohsin Abdulazeez, Dathar A. Hasan

    Published 2021-05-01
    “…Nowadays, data mining is an emerging research field in agriculture especially in the predicting and analysis of crop yield. This paper focuses on utilizing various data mining classification algorithms to predict the impact of various parameters such as area, season and production on the crop yield quality. …”
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  19. 99

    Evolutionary algorithms for predicting aboveground carbon stocks in mopane woodlands in Mozambique by Severino José Macôo, Evandro Nunes Miranda, Lucas Rezende Gomide

    Published 2025-12-01
    “…GARF predictions ranged from 2.910 to 19.459 MgC ha−1 (nRMSE = 0.427; MBE = 0.08), while GP showed a wider predictive range (1.721–23.503 MgC ha−1; nRMSE = 0.428; MBE = 2.731×10−17). …”
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  20. 100

    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad, Vaisali Chandrasekar, Omar Aboumarzouk, Ajay Vikram Singh, Sarada Prasad Dakua

    Published 2025-01-01
    “…Some chemicals act as hERG blockers, resulting in prolonged QT intervals. Predicting the binding capability of molecules with hERG channels is expected to reduce the burden of cardiotoxicity testing in drug evaluation. …”
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